St. Jude Cloud: A Pediatric Cancer Genomic Data-Sharing Ecosystem.
St. Jude Cloud: A Pediatric Cancer Genomic Data-Sharing Ecosystem.
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DOI：
10.1158/2159-8290.cd-20-1230
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发表时间：
2021-05
期刊：
影响因子：
28.2
通讯作者：
Zhang J
中科院分区：
文献类型：
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作者：
McLeod C;Gout AM;Zhou X;Thrasher A;Rahbarinia D;Brady SW;Macias M;Birch K;Finkelstein D;Sunny J;Mudunuri R;Orr BA;Treadway M;Davidson B;Ard TK;Chiao A;Swistak A;Wiggins S;Foy S;Wang J;Sioson E;Wang S;Michael JR;Liu Y;Ma X;Patel A;Edmonson MN;Wilkinson MR;Frantz AM;Chang TC;Tian L;Lei S;Islam SMA;Meyer C;Thangaraj N;Tater P;Kandali V;Ma S;Nguyen T;Serang O;McGuire I;Robison N;Gentry D;Tang X;Palmer LE;Wu G;Suh E;Tanner L;McMurry J;Lear M;Pappo AS;Wang Z;Wilson CL;Cheng Y;Meshinchi S;Alexandrov LB;Weiss MJ;Armstrong GT;Robison LL;Yasui Y;Nichols KE;Ellison DW;Bangur C;Mullighan CG;Baker SJ;Dyer MA;Miller G;Newman S;Rusch M;Daly R;Perry K;Downing JR;Zhang J
有效的数据共享是加速研究以提高儿科癌症和其他儿童灾难性疾病的诊断准确性、治疗效果和长期生存的关键。我们介绍了St. Jude Cloud（https：www.stjude.cloud），这是一个基于云的数据共享生态系统，用于访问，分析和可视化来自> 10，000名儿科癌症患者和长期幸存者以及>800名儿科镰状细胞患者的基因组数据。统一的基因组数据总计1.25 PB，包括12，104个全基因组，7，697个全外显子组和2，202个转录组。随着圣犹大前瞻性临床基因组学项目定期上传数据，该资源正在迅速扩大。生态系统中的三个相互关联的应用程序-基因组学平台，儿科癌症知识库和可视化社区-可以同时在云中执行高级数据分析并增强儿科癌症知识库。我们通过使用案例证明了生态系统的价值，这些案例通过基因表达谱对135种儿科癌症亚型进行分类，并绘制了35种儿科癌症亚型的突变特征。
Effective data sharing is key to accelerating research to improve diagnostic precision, treatment efficacy, and long-term survival of pediatric cancer and other childhood catastrophic diseases. We present St. Jude Cloud (https://www.stjude.cloud), a cloud-based data sharing ecosystem for accessing, analyzing and visualizing genomic data from >10,000 pediatric cancer patients and long-term survivors, and >800 pediatric sickle cell patients. Harmonized genomic data totaling 1.25 petabytes are freely available, including 12,104 whole genomes, 7,697 whole exomes and 2,202 transcriptomes. The resource is expanding rapidly with regular data uploads from St. Jude’s prospective clinical genomics programs. Three interconnected apps within the ecosystem—Genomics Platform, Pediatric Cancer Knowledgebase and Visualization Community—enable simultaneously performing advanced data analysis in the cloud and enhancing the pediatric cancer knowledgebase. We demonstrate the value of the ecosystem through use cases that classify 135 pediatric cancer subtypes by gene expression profiling and map mutational signatures across 35 pediatric cancer subtypes.